2 citations · 2 across the 5 of their papers we have counts for
5 papers
acia-workflows: Automated Single-cell Imaging Analysis for Scalable and Deep Learning-based Live-cell Imaging Analysis Workflows
Johannes Seiffarth, Keitaro Kasahara, Michelle Bund +7
Live-cell imaging (LCI) technology enables the detailed spatio-temporal characterization of living cells at the single-cell level, which is critical for advancing research in the l…
13CFLUX -- Third-generation high-performance engine for isotopically (non)stationary 13C metabolic flux analysis
Anton Stratmann, Martin Beyß, Johann F. Jadebeck +2
13C-based metabolic flux analysis (13C-MFA) is a cornerstone of quantitative systems biology, yet its increasing data complexity and methodological diversity place high demands on…
PyUAT: Open-source Python framework for efficient and scalable cell tracking
Johannes Seiffarth, Katharina Nöh
Tracking individual cells in live-cell imaging provides fundamental insights, inevitable for studying causes and consequences of phenotypic heterogeneity, responses to changing env…
Tracking one-in-a-million: Large-scale benchmark for microbial single-cell tracking with experiment-aware robustness metrics
J. Seiffarth, L. Blöbaum, R. D. Paul +6
Tracking the development of living cells in live-cell time-lapses reveals crucial insights into single-cell behavior and presents tremendous potential for biomedical and biotechnol…
Robust Approximate Characterization of Single-Cell Heterogeneity in Microbial Growth
Richard D. Paul, Johannes Seiffarth, Hanno Scharr +1
Live-cell microscopy allows to go beyond measuring average features of cellular populations to observe, quantify and explain biological heterogeneity. Deep Learning-based instance…